Integrated circuit design method, system and computer program product

ABSTRACT

A method executed at least partially by a processor includes creating a plurality of groups of paths from a plurality of paths in an integrated circuit (IC) layout diagram. Each group among the plurality of groups has a dominant feature among a plurality of features of the plurality of paths. The dominant features of the plurality of groups are different from each other. The method further includes testing at least one path in a group among the plurality of groups. The method also includes, in response to the testing indicating that the at least one path fails, modifying at least one of the IC layout diagram, at least a portion of at least one library having cells included in the IC layout diagram, or a manufacturing process for manufacturing an IC corresponding to the IC layout diagram.

BACKGROUND

An integrated circuit (IC) typically includes a number of semiconductordevices represented in an IC layout diagram. An IC layout diagram ishierarchical and includes modules which carry out higher-level functionsin accordance with the semiconductor device's design specifications. Themodules are often built from a combination of cells, each of whichrepresents one or more semiconductor structures configured to perform aspecific function. Cells having pre-designed layout diagrams, sometimesknown as standard cells, are stored in standard cell libraries(hereinafter “libraries” or “cell libraries” for simplicity) andaccessible by various tools, such as electronic design automation (EDA)tools, to generate, optimize and verify designs for ICs. At varioussteps during the IC design process, various checking and testing areperformed to make sure that ICs can be made and will function asdesigned.

BRIEF DESCRIPTION OF THE DRAWINGS

Aspects of the present disclosure are best understood from the followingdetailed description when read with the accompanying figures. It isnoted that, in accordance with the standard practice in the industry,various features are not drawn to scale. In fact, the dimensions of thevarious features may be arbitrarily increased or reduced for clarity ofdiscussion.

FIG. 1 is a functional flow chart of at least a portion of an IC designflow, in accordance with some embodiments.

FIGS. 2A-2F are schematic logic diagrams of various sections of an IClayout diagram with example paths, in accordance with some embodiments.

FIG. 2G is a schematic view of various extracted features of paths in anIC layout diagram, in accordance with some embodiments.

FIG. 3A is a flow chart of a process in a feature encoding and reductionoperation, in accordance with some embodiments.

FIG. 3B is a schematic data representation of example features in afirst feature reduction operation, in accordance with some embodiments.

FIG. 3C is a schematic view of a table including various numericalfeatures and categorical features with corresponding values in severalexample paths in a first encoding operation, in accordance with someembodiments.

FIG. 3D is a schematic view of a table including an example feature withcorresponding values in several example paths in a second encodingoperation, in accordance with some embodiments.

FIG. 3E is a schematic view of a table including an example feature withcorresponding values in several example paths in a third encodingoperation, in accordance with some embodiments.

FIG. 3F is a schematic view of a table including various numericalfeatures and categorical features with corresponding values in severalexample paths in a normalization operation, in accordance with someembodiments.

FIG. 3G is a schematic view of a table including various features withcorresponding correlation coefficients in a second feature reductionoperation, in accordance with some embodiments.

FIG. 3H is a schematic view of a reduced set of features of paths in anIC layout diagram, in accordance with some embodiments.

FIG. 4 is a flow chart of a process in feature clustering and pathgrouping operations, in accordance with some embodiments.

FIG. 5 is a flow chart of a process, in accordance with someembodiments.

FIG. 6 is a block diagram of an EDA system, in accordance with someembodiments.

FIG. 7 is a block diagram of an IC manufacturing system and an ICmanufacturing flow associated therewith, in accordance with someembodiments.

DETAILED DESCRIPTION

The following disclosure provides many different embodiments, orexamples, for implementing different features of the provided subjectmatter. Specific examples of components, materials, values, steps,operations, materials, arrangements, or the like, are described below tosimplify the present disclosure. These are, of course, merely examplesand are not intended to be limiting. Other components, values,operations, materials, arrangements, or the like, are contemplated. Forexample, the formation of a first feature over or on a second feature inthe description that follows may include embodiments in which the firstand second features are formed in direct contact, and may also includeembodiments in which additional features may be formed between the firstand second features, such that the first and second features may not bein direct contact. In addition, the present disclosure may repeatreference numerals and/or letters in the various examples. Thisrepetition is for the purpose of simplicity and clarity and does not initself dictate a relationship between the various embodiments and/orconfigurations discussed.

Further, spatially relative terms, such as “beneath,” “below,” “lower,”“above,” “upper” and the like, may be used herein for ease ofdescription to describe one element or feature's relationship to anotherelement(s) or feature(s) as illustrated in the figures. The spatiallyrelative terms are intended to encompass different orientations of thedevice in use or operation in addition to the orientation depicted inthe figures. The apparatus may be otherwise oriented (rotated 90 degreesor at other orientations) and the spatially relative descriptors usedherein may likewise be interpreted accordingly.

In an IC design process, one or more pre-manufacturing orpost-manufacturing verifications are performed for identifying apotential fault in an IC layout diagram or in an IC (chip) manufacturedin accordance with the IC layout diagram. In some embodiments, aplurality of paths in an IC layout diagram is grouped into a pluralityof groups. The paths in each group share a common dominant feature, suchas a timing feature, a logical feature, or a physical feature. A test isperformed for at least one path in each group. When a path fails thetest, the dominant feature associated with the corresponding group isidentified as related to a systematic defect. Based on the dominantfeature identified as related to a systematic defect, a correction forfixing the failing path is made to at least one of the IC layoutdiagram, a library having cells included in the IC layout diagram, or amanufacturing process. As a result, in at least one embodiment, it ispossible to fix or improve multiple paths sharing the same dominantfeature by a common correction strategy. In one or more embodiments, bygrouping paths by dominant features for testing, it is possible toidentify and correct various systematic defects which are not identifiedin other approaches.

FIG. 1 is a functional flow chart of at least a portion of an IC designflow 100 in accordance with some embodiments. The IC design flow 100utilizes one or more electronic design automation (EDA) tools forgenerating, optimizing and/or verifying a design of an IC before and/orafter manufacturing the IC. The EDA tools, in some embodiments, are oneor more sets of executable instructions for execution by a processor orcontroller or a programmed computer (e.g., system 600 (FIG. 6)) toperform the indicated functionality. In at least one embodiment, the ICdesign flow 100 is performed by a design house of an IC manufacturingsystem discussed herein with respect to FIG. 7.

At IC design generation operation 110, a design of an IC is provided bya circuit designer. In some embodiments, the design of the IC comprisesan IC schematic, i.e., an electrical diagram, of the IC. In someembodiments, the schematic is generated or provided in the form of aschematic netlist, such as a Simulation Program with Integrated CircuitEmphasis (SPICE) netlist. Other data formats, e.g., Verilog, fordescribing the design are usable in some embodiments. In someembodiments, a pre-layout simulation is performed on the design todetermine whether the design meets a predetermined specification. Whenthe design does not meet the predetermined specification, the IC isredesigned. In at least one embodiment, a pre-layout simulation isomitted.

At cell placement and routing operation 120, a layout diagram of the ICis generated based on the IC schematic. The cell placement and routingoperation 120 is referred to as Automatic Placement and Routing (APR) inat least one embodiment. The IC layout diagram comprises physicalpositions of various circuit elements of the IC as well as physicalpositions of various nets interconnecting the circuit elements. Forexample, the IC layout diagram is generated in the form of a GraphicDesign System (GDS) file. Other data formats, e.g., Design ExchangeFormat (DEF), for describing the design of the IC are within the scopeof various embodiments. In at least one embodiment, the IC layoutdiagram is generated by an EDA tool, such as an APR tool. The APR toolreceives the design of the IC in the form of a netlist as describedherein. The APR tool performs floor planning to identify circuitelements, which are to be electrically connected to each other and whichare to be placed in close proximity to each other, for reducing the areaof the IC and/or reducing time delays of signals travelling over theinterconnections or nets connecting the electrically connected circuitelements. In some embodiments, the APR tool performs partitioning todivide the design of the IC into a plurality of blocks or groups, suchas clock and logic groups. Example operations by the APR tool include,but are not limited to, a cell placement operation and a routingoperation.

In a cell placement operation, the APR tool performs cell placement.Cells configured to provide pre-defined functions and havingpre-designed layout diagrams are stored in one or more cell libraries,for example, in Library Exchange Format (LEF). LEF is a specificationthat includes design rules and information about cells in a library. Inat least one embodiment, LEF is used with DEF to represent a physicallayout of an IC being designed. The APR tool accesses various cells fromone or more cell libraries, and places the cells in an abutting mannerto generate an IC layout diagram corresponding to the IC schematic. Eachcell includes one or more circuit elements and/or one or more nets. Acircuit element is an active element or a passive element. Examples ofactive elements include, but are not limited to, transistors and diodes.Examples of transistors include, but are not limited to, metal oxidesemiconductor field effect transistors (MOSFET), complementary metaloxide semiconductor (CMOS) transistors, bipolar junction transistors(BJT), high voltage transistors, high frequency transistors, p-channeland/or n-channel field effect transistors (PFETs/NFETs) or the like,FinFETs, planar MOS transistors with raised source/drains, or the like.Examples of passive elements include, but are not limited to,capacitors, inductors, fuses, and resistors. Examples of nets include,but are not limited to, vias, conductive pads, conductive traces, andconductive redistribution layers, or the like.

In a routing operation, the APR tool performs routing to route variousnets interconnecting the placed circuit elements. The routing isperformed to ensure that the routed interconnections or nets satisfy aset of constraints. For example, the routing operation includes globalrouting, track assignment and detailed routing. During the globalrouting, routing resources used for interconnections or nets areallocated. For example, the routing area is divided into a number ofsub-areas, pins (or terminals) of the placed circuit elements are mappedto the sub-areas, and nets are constructed as sets of sub-areas in whichinterconnections are physically routable. During the track assignment,the APR tool assigns interconnections or nets to correspondingconductive layers of the IC layout diagram. During the detailed routing,the APR tool routes interconnections or nets in the assigned conductivelayers and within the global routing resources. For example, detailed,physical interconnections are generated within the corresponding sets ofsub-areas defined at the global routing and in the conductive layersdefined at the track assignment. After the routing operation, the APRtool outputs the IC layout diagram including the placed circuit elementsand routed nets. The described APR tool is an example. Otherarrangements are within the scope of various embodiments. For example,in one or more embodiments, one or more of the described operations areomitted or one or more additional operations are added before, during,or after the described operations.

In some embodiments, one or more verifications are performed after thecell placement and routing operation 120. Example verifications include,but are not limited to, a layout-versus-schematic (LVS) check, and adesign rule check (DRC). Other verification processes are usable inother embodiments.

An LVS check is performed to ensure that the generated IC layout diagramcorresponds to the design of the IC. Specifically, an LVS checking tool,i.e., an EDA tool, recognizes electrical components as well asconnections therebetween from the patterns of the generated IC layoutdiagram. The LVS checking tool then generates a layout netlistrepresenting the recognized electrical components and connections. Thelayout netlist generated from the IC layout diagram is compared, by theLVS checking tool, with the schematic netlist of the design of the IC.If the two netlists match within a matching tolerance, the LVS check ispassed. Otherwise, correction is made to at least one of the IC layoutdiagram or the design of the IC by returning the process to at least oneof the IC design generation operation 110 or the cell placement androuting operation 120.

A DRC is performed, e.g., by an EDA tool, to ensure that the IC layoutdiagram satisfies certain manufacturing design rules, i.e., to ensuremanufacturability of the IC. If one or more design rules is/areviolated, correction is made to at least one of the IC layout diagram orthe design of the IC by returning the process to at least one of the ICdesign generation operation 110 or the cell placement and routingoperation 120. Examples of design rules include, but are not limited to,a width rule which specifies a minimum width of a pattern in the IClayout diagram, a spacing rule which specifies a minimum spacing betweenadjacent patterns in the IC layout diagram, an area rule which specifiesa minimum area of a pattern in the IC layout diagram, etc.

At resistance and capacitance (RC) extraction operation 130, an RCextraction is performed, e.g., by an EDA tool, to determine parasiticparameters, e.g., parasitic resistance and parasitic capacitance, ofcomponents in the IC layout diagram for timing simulations in one ormore subsequent operations.

At static timing analysis (STA) operation 140, an EDA tool estimatesdelays in a plurality of paths in the IC layout diagram. Input data forthe STA operation 140 include, but are not limited to, the IC layoutdiagram, the parasitic parameters extracted by the RC extractionoperation 130, cell delays obtained from one or more cell librarieshaving cells included in the IC layout diagram. Output data from the STAoperation 140 are included in a timing report described herein. In atleast one embodiment, the STA operation 140 is performed without asimulation of operation of an IC corresponding to the IC layout diagram.In at least one embodiment, when the delays estimated in the STAoperation 140 for one or more paths fail to meet corresponding timingrequirements, correction is made to at least one of the IC layoutdiagram or the design of the IC by returning the process to at least oneof the IC design generation operation 110 or the cell placement androuting operation 120.

At Automatic Path Selection and Testing (APST) operation 150, the pathsin the IC layout diagram are grouped and test patterns are generated forthe grouped paths. In some embodiments, the APST operation 150 isperformed at least partially by an EDA tool. An exploded schematic viewshowing further operations of the APST operation 150 in accordance withsome embodiments is also illustrated in FIG. 1. Input data for the APSToperation 150 include one or more of the IC schematic 113 output fromthe IC design generation operation 110, the IC layout diagram 123 outputfrom the cell placement and routing operation 120, and the timing report143 from the STA operation 140. In the example configuration in FIG. 1,the APST operation 150 comprises a feature extraction operation 152, afeature encoding and reduction operation 153, a feature clusteringoperation 154, a cluster analysis and path grouping operation 155, andan Automatic Test Pattern Generation (ATPG) operation 156.

At the feature extraction operation 152, a plurality of features of thepaths in the IC layout diagram is extracted, as described with respectto FIGS. 2A-2G.

At the feature encoding and reduction operation 153, the extractedfeatures are encoded and reduced to obtain a reduced set of features, asdescribed with respect to FIGS. 3A-3G.

At the feature clustering operation 154, the paths of the IC layoutdiagram are divided into a plurality of clusters, as described withrespect to FIG. 4.

At the cluster analysis and path grouping operation 155, the clustersare analyzed and grouped into a plurality of groups with associatedunique dominant features, as described with respect to FIG. 4.

At the ATPG operation 156, one or more ATPG methods or algorithms areused to generate test patterns for one or more paths in each group, asdescribed herein.

At testing operation 160, a test is performed for one or more paths ineach group, using the test patterns generated by the ATPG operation 156to determine whether the IC layout diagram or an actual IC manufacturedin accordance with the IC layout diagram meets a predeterminedspecification of one or more timing requirements. In at least oneembodiment, the test comprises a post-layout simulation, e.g., performedby an EDA tool, to simulate an operation of an IC corresponding to theIC layout diagram. In some embodiments, the test is performed byAutomatic Test Equipment (ATE) having hardware structures, such asprobes, to electrically couple to an actual IC (chip) fabricated inaccordance with the IC layout diagram, for testing operation of theactual IC. In one or more embodiments, the test at the testing operation160 comprises both a post-layout simulation by an EDA tool and a testperformed by ATE on an actual IC. When the IC layout diagram and/or anactual IC fabricated based on the IC layout diagram pass the test,additional verification processes are performed, or ICs are fabricatedbased on the IC layout diagram.

At modification operation 170, correction is made when the IC layoutdiagram and/or an actual IC fabricated based on the IC layout diagramfail the test at the testing operation 160. In some embodiments,correction is made to at least one of the IC layout diagram or thedesign of the IC by returning the process to at least one of the ICdesign generation operation 110 or the cell placement and routingoperation 120. The correction to the design of the IC at the IC designgeneration operation 110 results in corresponding correction to the IClayout diagram at the cell placement and routing operation 120. In someembodiments, correction is made to one or more cell libraries havingcells included in the IC layout diagram. The correction to the one ormore cell libraries results in corresponding correction to the IC layoutdiagram at the cell placement and routing operation 120. In someembodiments, correction is made to a manufacturing process formanufacturing an IC corresponding to the IC layout diagram. The ICdesign flow 100 in FIG. 1 is an example. In some embodiments, the ICdesign flow 100 includes one or more further operations, and/or one ormore of the described operations are omitted.

FIGS. 2A-2F are schematic logic diagrams of various sections of an IClayout diagram with example paths, in accordance with some embodiments.FIG. 2G is a schematic view showing various extracted features of pathsin an IC layout diagram, in accordance with some embodiments.

FIG. 2A is a schematic logic diagrams of a section 200A of an IC layoutdiagram, with path 1 in accordance with some embodiments. The section200A comprises a plurality of logic gates 201-204, and a plurality ofnets (or wires) 205-210 which couple logic gates 201-204 with each otherand with two flip-flops FF1, FF2. For simplicity, each logic gate isassumed to be a cell. Path 1 comprises net 205, cell 201, net 206, cell204 and net 207 coupled serially between flip-flops FF1, FF2. In atleast one embodiment, path 1 is identified in the timing report 143output from the STA operation 140. Features of path 1 include featuresof nets 205, 206, 207 and features of cells 201, 204 in path 1.

Example features of a net include, but are not limited to, “physical netlength in metal layer,” “total physical net length,” “number of vias inwire (or net),” “net delay,” “slew-ratio,” “layout shape,” or the like.The feature “physical net length in metal layer” indicates a physicallength of a section of the net arranged in a metal layer, such as M0,M1, M2 or the like. The feature “total physical net length” indicates atotal physical length of the net in all metal layers in which the net isarranged. The feature “number of vias in wire (or net)” indicates anumber of vias that couple different segments of the net in differentmetal layers together. The feature “net delay” indicates a time delay ofa signal travelling through the net due to the parasitic capacitance andparasitic resistance of the net. The feature “slew-ratio” indicates howfast or slow a leading edge or a trailing edge of a signal rises orfalls. The feature “layout shape” indicates a shape of the net. Exampleshapes of a net include, but are not limited to, L-shape, I-shape,T-shape, or the like. Other features of a net are within the scopes ofvarious embodiments.

Example features of a cell include, but are not limited to, “drivingstrength,” “VT type,” “number of inputs,” “number of outputs,” “functiontype,” “number of transistors,” “height,” “pitch,” “layout shape,”“sensitivity delay” or the like. The feature “driving strength”indicates a designed load of the cell. The feature “VT type” indicates atype of threshold voltage (VT) at which transistors in the cell areturned ON or OFF. Example VT types include, but are not limited to, highthreshold voltage (HVT), low threshold voltage (LVT), ultralow thresholdvoltage (ULVT), standard threshold voltage (SVT). Generally, cells withlower threshold voltages are faster but consume more power than cellswith higher threshold voltages. The feature “number of inputs” indicatesthe number of inputs of the cell. The feature “number of outputs”indicates the number of outputs of the cell. The feature “function type”indicates a logic type of the cell. Example logic types include, but arenot limited to, AOI (AND-OR-Invert), AND, XOR, OR, NAND, NOR, INV(Invert) or the like. The feature “number of transistors” indicates thenumber of transistors in the cell. The feature “height” indicates aheight of the cell in a direction along gate regions of transistors inthe cell. The feature “pitch” indicates a pitch between adjacent gateregions. The feature “layout shape” indicates a shape of a net insidethe cell. The feature “sensitivity delay” indicates a time delay of asignal travelling through the cell. Other features of a cell are withinthe scopes of various embodiments. Further example features of paths aredescribed with respect to FIG. 2G.

FIG. 2B is a schematic logic diagrams of a section 200B of an IC layoutdiagram, with path 2 in accordance with some embodiments. In the exampleconfiguration in FIG. 2B, nets 211-214 along path 2 have physical netlengths in metal layer M3 being 50 units, 30 units, 100 units and 200units, respectively. The physical net lengths of nets 211-214 in metallayer M3 are greater than in other metal layers. In other words, nets211-214 along path 2 are dominantly arranged in metal layer M3, or path2 is dominated by nets in metal layer M3. Because nets 211-214 aredominantly arranged in metal layer M3, path 2 will be affected more by avariation in metal layer M3 compared to other paths not dominated bymetal layer M3. When there is a variation in metal layer M3, smalldelays along nets 211-214 in path 2 will accumulate into a larger,easier to detect delay. In some embodiments as described herein, bygrouping paths based on a dominant feature, such as metal layer M3 forpath 2 or another feature described with respect to FIGS. 2C-2G, andtesting the grouped paths, it is possible to identify and fix smalldelay defects (SDDs).

FIG. 2C is a schematic logic diagrams of a section 200C of an IC layoutdiagram, with path 3 in accordance with some embodiments. In the exampleconfiguration in FIG. 2C, cells 215-218 are arranged along path 3. Cells215, 216, 218 are configured from transistors having a low thresholdvoltage (LVT), and cell 217 is configured from transistors having astandard threshold voltage (SVT). In other words, the cells along path 3are dominantly configured as LVT cells, or path 3 is dominated by LVTcells.

FIG. 2D is a schematic logic diagrams of a section 200D of an IC layoutdiagram, with path 4 in accordance with some embodiments. In the exampleconfiguration in FIG. 2D, cells 219-221 are arranged along path 4. Eachof cells 219-221 is configured to have three inputs. In other words, thecells along path 4 are dominantly configured as 3-input cells, or path 4is dominated by 3-input cells.

FIG. 2E is a schematic logic diagrams of a section 200E of an IC layoutdiagram, with path 5 in accordance with some embodiments. In the exampleconfiguration in FIG. 2E, nets 222-226 are arranged along path 5. Thenumbers of vias in nets 222-226 are 5, 59, 137, 8, and 23, respectively.The total number of vias in the nets of path 5 is greater than anaverage total number of vias in the plurality of paths of the IC layoutdiagram. In other words, path 5 is dominated by the number of vias inthe path.

FIG. 2F is a schematic logic diagrams of a section 200F of an IC layoutdiagram, with path 6 in accordance with some embodiments. In the exampleconfiguration in FIG. 2F, nets 227-230 arranged along path 6 havephysical net lengths in metal layer M5 being 121.3, 68.5, 259.4 and97.6, respectively. The total physical net lengths of the nets of path 6in metal layer M5 is greater than other paths. In other words, path 6 isdominated by the physical net length in metal layer M5.

FIG. 2G is a schematic view of a feature list 200G showing variousextracted features of paths in an IC layout diagram, in accordance withsome embodiments. The feature list 200G is an example of a result of thefeature extraction operation 152. The feature list 200G comprises one ormore of timing features 240, logical features 250, and physical features260. The feature list 200G is not exhaustive, and other features arewithin the scopes of various embodiments.

One or more of the timing features 240 are obtained as a result of theSTA operation 140, included in the timing report 143 supplied to theAPST operation 150, and then extracted from the timing report 143 by thefeature extraction operation 152. An example feature is slack 241. Slackof a path is an amount of delay tolerable in a path before a timingconstraint is violated. A negative value of slack indicates that thepath already violates the timing constraint. A zero value of slackindicates that an IC corresponding to the IC layout diagram is operable,but no timing margin is available. A positive value of slack indicatesthat the IC is operable with a timing margin. An IC design flow attemptsto achieve positive, or at least non-negative, values of slack in allpaths.

One or more of the timing features 240 are obtained from a library. Anexample is library setup/hold time 242. The library setup/hold time 242is a predetermined or known timing parameter of a cell and is retrievedfrom a library corresponding to the cell. In at least one embodiment,the library setup/hold time 242 is extracted from the library in thefeature extraction operation 152. In one or more embodiments, thelibrary setup/hold time 242 is included, at the STA operation 140, intothe timing report 143, and then sent to the APST operation 150 forextraction in the feature extraction operation 152.

One or more of the logical features 250 are extracted from the ICschematic 113, e.g., a Verilog netlist.

One or more of the physical features 260 are extracted from the IClayout diagram 123, e.g., from one or more DEF and/or LEF filescontaining the IC layout diagram 123.

FIG. 3A is a flow chart of a process 300A in the feature encoding andreduction operation 153, in accordance with some embodiments. Theprocess 300A comprises a first feature reduction operation 310, afeature encoding operation 320, and a second feature reduction operation330.

At the first feature reduction operation 310, one or more features amongthe plurality of features extracted by the feature extraction operation152 are removed based on data variation of the features across theplurality of paths of the IC layout diagram. The first feature reductionoperation 310 is described herein with respect to FIG. 3B. In at leastone embodiment, the first feature reduction operation 310 is omitted.

At the beginning of the feature encoding operation 320, the featuresremaining after the first feature reduction operation 310 are dividedinto numerical features 321 and categorical features 322. A numericalfeature is a feature having numerical values. A categorical feature is afeature having non-numerical values. Example non-numerical valuesinclude, but are not limited to, strings of characters. Example ofnumerical features and categorical features are described herein in withrespect to FIG. 3C. Because numerical values of the numerical features321 are ready for further calculations, the numerical features 321 arenot subjected to one or more of first-third encoding operations 323-325.To the contrary, non-numerical values of the categorical features 322are not ready for further calculations, and are converted or encoded toobtain corresponding converted numerical values in one or more of thefirst through third encoding operations 323-325 in the feature encodingoperation 320.

At the first encoding operation 323, a non-numerical value correspondingto a name of a pin or an instance (e.g., from a netlist) is encoded orconverted into a corresponding converted numerical value, based on oneor more hierarchy levels associated with the pin or instance, asdescribed with respect to FIG. 3C.

At the second encoding operation 324, a non-numerical valuecorresponding to features of a cell is split into a function type and aprocess parameter, and encoded or converted into corresponding convertednumerical values, as described with respect to FIG. 3D.

At the third encoding operation 325, a non-numerical value correspondingto a further feature is encoded or converted into a correspondingconverted numerical value, using ordinal encoding, as described withrespect to FIG. 3E.

At a normalization operation 326 of the feature encoding operation 320,the numerical values of the numerical features and the convertednumerical values of the categorical features are normalized, asdescribed with respect to FIG. 3F. The described operations in thefeature encoding operation 320 are example. Other arrangements forconverting non-numerical values to converted numerical values are withinthe scopes of various embodiments.

At the second feature reduction operation 330, based on the normalizedvalues output from the normalization operation 326, one or more featuresare further removed based on correlation with slack, as described withrespect to FIG. 3G. As a result, a reduced set of features is obtained,as described with respect to FIG. 3H.

FIG. 3B is a schematic data representation 300B of example features inthe first feature reduction operation 310, in accordance with someembodiments. For simplicity, schematic data representations of a limitednumber of example features “slack,” “clock uncertainty,” “LVT cells,”“net length” and “net area” are illustrated in FIG. 3B, in the form ofcorresponding graphs 311-315. The abscissa of each graph 311-315indicates the number N of paths in the plurality of paths of the IClayout diagram. The ordinate of each graph 311-315 indicates a value ofthe corresponding feature for each of the N paths. The datapresentations are for illustrative purposes, and are omitted in one ormore embodiments.

In some embodiments, all features extracted by the feature extractionoperation 152 are analyzed to determine variations of the featuresacross the plurality of paths of the IC layout diagram. Features thatshow no variation across the N paths are removed from further analysis.For example, as shown at graph 312, the value of “clock uncertainty”remains unchanged across the N paths of the IC layout diagram. As aresult, “clock uncertainty” is removed from further analysis. Otherexample features “slack,” “LVT cells,” “net length” and “net area” havevalues that vary across the N paths, and are maintained for furtheranalysis. In at least one embodiment, features with incompleteinformation are also removed from further analysis.

In at least one embodiment, the described removal of one or morefeatures based on data variation and/or information incompleteness is asimple way to reduce the number of features subject to further analysis,thereby reducing the calculation workload.

FIG. 3C is a schematic view of a table 300C including various numericalfeatures 340 and categorical features 345 with corresponding values inseveral example paths Path #1 through Path_#4 among the N paths of theIC layout diagram, in accordance with some embodiments. The numericalfeatures 340 include numerical features 341-344 which are timingfeatures corresponding to one or more of the timing features 240described with respect to FIG. 2G. As shown in FIG. 3C, the numericalfeatures 341-344 have numerical values for each of Path_#1 throughPath_#4. In this example, the numerical values of the numerical features341-344 are delay times. The categorical features 345 includecategorical features 346-348 which are logical features corresponding toone or more of the logical features 250 described with respect to FIG.2G. As shown in FIG. 3C, the categorical features 346-348 havenon-numerical values which are presented in the form of strings ofcharacters. In this example, the strings of characters of thecategorical features 346-348 indicate pin or instance names, cellfeatures, and clock, respectively. The list of features shown in FIG. 3Cis an example and is not exhaustive.

Non-numerical values of the categorical feature 346 are shown in moredetail in the enlarged view in FIG. 3C, to provide an example of pin orinstance name encoding in the first encoding operation 323. Eachnon-numerical value of the categorical feature 346 indicates a name of apin or an instance in a corresponding one of Path_#1 through Path_#4.Each pin or instance name is presented in the form of a string ofcharacters which includes one or more slash characters “/” to indicate aplurality of hierarchy levels associated with the pin or instance. Inthe example configuration in FIG. 3C, there are nine hierarchy levels349-357 in each of the non-numerical values of the categorical feature346. The hierarchy level 349 is the highest level, followed by the level350, and so on, down to the lowest level 357. The string segment in eachof the hierarchy levels 349-357 is encoded to be a number, in accordancewith a predetermined encoding scheme. For example, the string segment“u12_logic” at the hierarchy level 355 is encoded to a number “1” forall Path_#1 through Path_#4. Similarly, the string segment at each ofthe hierarchy levels 349-354 is encoded to a number “1” for all Path_#1through Path_#4. At the hierarchy levels 356, 357, the string segmentsin the Path_#1 through Path_#4 are different and, therefore, are encodedto different numbers. Specifically, at the hierarchy level 356, thestring segment “ucpu3_arb” is the same in Pat_#1 and Path_#2 and isencoded to “21” in Path_#1 and Path_#2, whereas the string segment“uarb_1c” is the same in Path_#3 and Path_#4 and is encoded to “10” inPath_#3 and Path_#4. At the hierarchy level 357, the string segment isthe same in Path_#1 and Path_#2 and is encoded to “60” in Path_#1 andPath_#2, whereas different string segments in Path_#3 and Path_#4 areencoded to “40” and “50,” respectively. As a result of the described pinor instance name encoding operation 323, the non-numerical values of thecategorical feature 346 for Path_#1 through Path_#4 are encoded tocorresponding converted numerical values “11111112160,” “11111112160,”“11111111040,” and “11111111050,” respectively, as also illustrated inFIG. 3F.

FIG. 3D is a schematic view of a table 300D including the categoricalfeature 347 with corresponding non-numerical values being encoded in thesecond encoding operation 324, in accordance with some embodiments. Thecategorical feature 347 includes several features of a cell, and issplit into further categorical features 360, 361 indicating a cellfunction type and a process parameter of the cell, respectively. Eachnon-numerical value or a string of characters of the categorical feature347 is also split into shorter segments corresponding to the categoricalfeatures 360, 361. For example, the non-numerical value or a string ofcharacters “DFRPQD4BWP300H8P63PDULVT” of the categorical feature 347 issplit into a string segment 362 “DFRPQ,” a string segment 363 “D4,” astring segment 364 “BWP300H8P63PD,” and a string segment 365 “ULVT.” Thestring segment 362 “DFRPQ” indicates the cell function type being aflip-flop, and is converted to a non-numerical value 366 “Flop” of thecategorical feature 360. The string segment 363 “D4” indicates thedriving strength of the cell. In the example in FIG. 3D, the drivingstrength is not shown further for simplicity. However, it is within thescopes of one or more embodiments to include this feature in furtheranalysis. The string segment 364 “BWP300H8P63PD” indicates the processparameter, and is converted to a non-numerical value 367 “BWP300H8P63P”of the categorical feature 361. The string segment 365 “ULVT” indicatesthe threshold voltage of the cell. In the example in FIG. 3D, thethreshold voltage is not shown further for simplicity. However, it iswithin the scopes of one or more embodiments to include this feature infurther analysis. Similarly, to the first encoding operation 323, eachof the non-numerical values 366, 367 is encoded to be a number, inaccordance with a predetermined encoding scheme. For example, thenon-numerical value 366 “Flop” is encoded to a corresponding convertednumerical value 368 “1,” and the non-numerical value 367 “BWP300H8P63P”is encoded to a corresponding converted numerical value 369 “1.” Theother non-numerical values, collectively indicated in FIG. 3D at 370, ofthe categorical feature 347 are similarly split and encoded tocorresponding converted numerical values, collectively indicated in FIG.3D at 371.

FIG. 3E is a schematic view of a table 300E including the categoricalfeature 348 with corresponding non-numerical values being encoded in thethird encoding operation 325, in accordance with some embodiments.Similarly, to the first encoding operation 323, each of thenon-numerical values of the categorical feature 348 is encoded to be anumber, in accordance with a predetermined encoding scheme, e.g., anordinal encoding. For example, the non-numerical value “CA72_ACLK” isencoded to a corresponding converted numerical value “1.” The othernon-numerical values of the categorical feature 348 are similarlyencoded, as indicated in FIG. 3E.

FIG. 3F is a schematic view of a table 300F including various numericalfeatures 340 and categorical features 345 with corresponding numericaland converted numerical values in the normalization operation 326, inaccordance with some embodiments. The table 300F includes numericalvalues of the numerical features 340, collectively indicated in FIG. 3Fat 372, and converted numerical values of the categorical features 345,collectively indicated in FIG. 3F at 373. The numerical values 372 ofthe numerical features 340 are the same as corresponding numericalvalues in the table 300C. The converted numerical values 373 of thecategorical features 345 are obtained by encoding or converting thecorresponding non-numerical values of the categorical features 345 inthe first-third encoding operations 323-325, as described with respectto FIGS. 3C-3E. The numerical and converted numerical values 372, 373are normalized to obtain corresponding normalized values 380. Forexample, the numerical values “0.000228,” “0.007996,” “0.005491” and“0.006957” of the numerical feature 341 (hereinafter feature LIB) arenormalized to obtain corresponding normalized values “0.01502,”“0.08514,” “0.04104” and “0.05694.”

As a result of the normalization operation 326, each feature has aplurality of normalized values corresponding to N paths of the IC layoutdiagram. For example, feature LIB has normalized values “0.01502,”“0.08514,” “0.04104” and “0.05694” for Path_#1 through Path_#4.Likewise, the feature slack also has normalized values (not shown) forPath_#1 through Path_#4. These two sets of normalized values for thefeatures LIB and slack are used to determine a correlation coefficientbetween the features LIB and slack in the second feature reductionoperation 330. In at least one embodiment, a reason why slack is chosento be the base feature for determining correlation with the otherfeatures is because testing is done for timing verification and/orbecause the STA operation 140 in one or more embodiments is configuredfor slack optimization. Base features, other than slack, for determiningcorrelation are within the scopes of various embodiments.

In some embodiments, the following formula (1) is used to calculate acorrelation coefficient

$\begin{matrix}{r_{xy} = \frac{\sum_{i = 1}^{N}{\left( {x_{i} - \overset{\_}{x}} \right)\left( {y_{i} - \overset{\_}{y}} \right)}}{\sqrt{\sum_{i = 1}^{N}\left( {x_{i} - \overset{\_}{x}} \right)^{2}}\sqrt{\sum_{i = 1}^{N}\left( {y_{i} - \overset{\_}{y}} \right)^{2}}}} & (1)\end{matrix}$

where r_(xy) is the correlation coefficient, x_(i) is the normalizedvalue of slack at the i-th path among the N paths of the IC layoutdiagram, y_(i) is the normalized value of another feature, e.g., LIB, atthe i-th path, x is the mean of all normalized values of slack acrossall N paths, and y is the mean of all normalized values of LIB acrossall N paths. The correlation coefficients between slack and otherfeatures are similarly calculated, and example results are given in FIG.3G.

FIG. 3G is a schematic view of a table 300G including various featureswith corresponding correlation coefficients in the second featurereduction operation 330, in accordance with some embodiments. Asillustrated at 391, the correlation coefficient calculated as describedherein between LIB and slack across N paths of the IC layout diagram is“0.178542” in this example. In the table 300G, the correlationcoefficients are sorted in the descending order.

Features corresponding to the correlation coefficients within apredetermined range 393 are removed from further analysis. In someembodiments, the predetermined range is between −0.15 and 0.15. Featureswith the correlation coefficients in this predetermined range aroundzero are considered to have little or no correlation with slack. Whenthere is a variation in such a feature, e.g., ViaCount (the number ofvias in a path) as indicated at 394, slack will be unlikely affected dueto the little or no correlation between ViaCount and slack. In otherwords, in this specific example, ViaCount due to its low correlationwith slack is considered to have little or no significant effect onslack and timing performance. The feature ViaCount is therefore removedfrom further analysis. In at least one embodiment, this removal reducesthe calculation workload at further, subsequent analysis. Otherpredetermined ranges for removing features considered to have little orno correlation with slack are within the scopes of various embodiments.

Features corresponding to the correlation coefficients outside thepredetermined range 393 are retained for further analysis. For example,features corresponding to the correlation coefficients in ranges 395 and396 respectively above and below the predetermined range 393 areretained for further analysis. Features corresponding to the correlationcoefficients in the range 395 have positive correlation with slack,which means when a value of one of these features is increased, there isa likelihood that slack is also increased. Features corresponding to thecorrelation coefficients in the range 396 have negative correlation withslack, which means when a value of one of these features is increased,there is a likelihood that slack is decreased. Due to the sufficientcorrelation with slack, the features corresponding to the correlationcoefficients in the ranges 395, 396 are considered to have potentialeffect on slack and timing performance. These features are retained forfurther analysis, and together constitute a reduced set of features anexample of which is given in FIG. 3H.

FIG. 3H is a schematic view showing a reduced set 300H of features ofpaths in an IC layout diagram, in accordance with some embodiments. Thereduced set 300H lists all extracted features as in the feature list200G in FIG. 2G. However, features that have been removed by the firstfeature reduction operation 310 based on data variation and the secondfeature reduction operation 330 based on correlation with slack areindicated as being stricken through in the reduced set 300H. The reducedset 300H is an example result of the feature encoding and reductionoperation 153. In at least one embodiment, the encoding processing inthe feature encoding and reduction operation 153 makes it possible toanalyze categorical features in a manner similar to numerical featuresas described herein. In at least one embodiment, the feature reductionin the feature encoding and reduction operation 153 makes it possible toremove features that are unlikely to affect timing performance and toreduce calculation workload.

FIG. 4 is a flow chart of a process 400 in the feature clusteringoperation 154 and cluster analysis and path grouping operation 155, inaccordance with some embodiments. The feature clustering operation 154comprises operations 410, 420 with which the paths of the IC layoutdiagram are clustered or divided into a plurality of clusters. Thecluster analysis and path grouping operation 155 comprises operations430, 440, 450 with which the clusters are analyzed and grouped into aplurality of groups with associated unique dominant features.

At operation 410, a number of clusters into which the N paths of the IClayout diagram are to be divided is determined. In some embodiments, thefollowing formula (2) is used to calculate the number k of clusters:

k= ²√{square root over (N/2)}  (2)

At operation 420, a clustering algorithm is applied for clustering the Npaths. In some embodiments, the clustering algorithm applied inoperation 420 is K-means clustering. K-means clustering is used inunsupervised learning. Other clustering algorithms are within the scopesof various embodiments.

Data for K-means clustering include the reduced set 300H of m featuresobtained as a result of the feature encoding and reduction operation153, and the normalized values of the m features in the N paths obtainedas a result of the normalization operation 326. Each path is presentedas a data point including m normalized values of the m features. Theobjective of K-means clustering is to cluster the N data points into kclusters S₁ . . . S_(k) in an iterative process to achieve the followingminimization:

$\begin{matrix}{\underset{S}{\arg\mspace{11mu}\min}{\sum\limits_{i = 1}^{k}{\frac{1}{2{S_{i}}}{\sum\limits_{x,{y \in S_{i}}}{{x - y}}^{2}}}}} & (3)\end{matrix}$

At operation 430, a biasing of each of the m features is calculated ineach of the k clusters, for example, using the following formula:

CB _(nx)=(CM _(nx) −DS _(x))/DS _(x)   (4)

where CB_(nx) is a biasing of feature x in cluster n, CM_(nx) is a meanvalue of feature x in the paths in cluster n, and DS_(x) is a mean valueof feature x in all N paths.

At operation 440, based on the biasing of each feature in each clustercalculated at operation 430, a dominant feature is determined for eachcluster. For example, for each cluster n, when (CB_(nx)/Σ_(i=1)^(m)CB_(n)i) is greater than a predetermined threshold X, cluster n isbiased toward feature x, and feature x is determined as the dominantfeature of cluster n. In some embodiments, the threshold X fordetermining whether cluster n is biased toward feature x is a value from40% to 60%. Any other values of the threshold X are within the scopes ofvarious embodiments. For example, in one or more embodiments, thethreshold X is 70%, 85%, or 90%. In at least one embodiment with thethreshold X being greater than 50%, there is a maximum of one featuresatisfying the condition (CB_(nx)/Σ_(i=1) ^(m)CB_(n)i)>X in a cluster.In at least one embodiment with the threshold X being 50% or lower,there is a potential situation where more than one features satisfy thecondition (CB_(nx)/Σ_(i=1) ^(m)CB_(n)i)>X in a cluster. In such asituation, the cluster is determined to be dominated by more than onefeatures.

When no cluster has (CB_(nx)/Σ_(i=1) ^(m)CB_(n)i) greater than thepredetermined threshold X for feature x, the cluster with the greatest(CB_(nx)/Σ_(i=1) ^(m)CB_(n)i) is determined to have feature x as thedominant feature. This determination is applicable even when the clusterwith the greatest (CB_(nx)/Σ_(i=1) ^(m)CB_(n)i) is already determined tohave a dominant feature other than feature x. It is within the scope ofone or more embodiments that a cluster has more than one dominantfeatures. It is also within the scope of one or more embodiments that afeature is determined to be a dominant feature of more than oneclusters.

As a result of the operation 440, each of the k clusters has at leastone dominant feature being one of the m features, and each of the mfeatures is determined as a dominant feature of at least one of the kclusters.

At operation 450, m groups of paths are created from the k clusters, sothat each group has a unique dominant feature that is different fromdominant features of the other groups. For example, when, among the kclusters, a first feature has been determined to be the dominant featureof only one cluster, then that cluster is designated as the group havingthe first feature as the dominant feature. Further, when, among the kclusters, a second feature has been determined to be the dominantfeature of more than one clusters, such clusters are merged togetherinto the group having the second feature as the dominant feature. Insome embodiments, each path is included in one group, resulting in aplurality of non-overlapping groups. In a further example, where acluster has been determined to have several dominant features, thecluster is merged into several groups corresponding to the severaldominant features. As a result, at least one embodiment includes apotential situation in which a path is included in more than one groups.

In some embodiments, as a result of the operation 450 of the clusteranalysis and path grouping operation 155, the N paths of the IC layoutdiagram are grouped into m groups with m different dominant featureseach corresponding to one of the m features in the reduced set 300H offeatures obtained by the feature encoding and reduction operation 153. Adominant feature of a group is a feature by which the paths in the groupare dominated, as described with respect to FIGS. 2B-2F. For example,the paths in a group having metal layer M3 as the dominant feature aredominated by metal layer M3, as described with respect to FIG. 2B.

As can be seen in FIG. 4, after the operation 450 of the clusteranalysis and path grouping operation 155, the process proceeds to theATPG operation 156 where one or more ATPG methods or algorithms are usedto generate test patterns for one or more paths in each group for whicha dominant feature has been designated. A specific example is describedherein for a group having metal layer M3 as the dominant feature.

Specifically, the paths in the group having metal layer M3 as thedominant feature are identified in a report, e.g., a netlist, from thecluster analysis and path grouping operation 155 to the ATPG operation156 for subsequent testing. In practice, not all paths in the group aretestable, due the large number of paths or a specific nature of a paththat renders the path untestable. For all testable paths in the group,the ATPG operation 156 generates corresponding test patterns. Thegenerated test patterns vary from path to path depending on, forexample, the types and/or number of cells or gates on the path, the teststrategy, or the ATPG method or algorithm used to generate the testpattern. An example ATPG strategy used in one or more embodiments ispath delay ATPG which is used to generate both robust and non-robustpath delay test patterns. As described herein with respect to FIG. 1,the generated test patterns are used in a simulation for IC designverification before fabrication, and/or in an ATE for testing an actual,fabricated IC.

When one of the paths fails the test, because the failed path wasidentified by the APST operation 150 as belonging to a group with thedominant feature being metal layer M3, it is possible in one or moreembodiments to select a correction strategy related to the dominantfeature, i.e., metal layer M3, to fix or improve timing performance ofthe failed path. Such correction strategy related to metal layer M3 isexpected in at least one embodiment to also improve performance of otherpaths in the same group dominated by metal layer M3. As a result, it ispossible in some embodiments to target or improve multiple paths with asingle correction strategy, thereby saving time and efforts in the ICdesign and/or fabrication process. The above advantage is achievable notonly at a simulation before signing-off for fabrication or when testingan actual, fabricated IC, but also at an earlier stage. For example, inat least one embodiment, identifed groups of paths with designateddominant features are relied on to define a strategy for fixing timingissues discovered by the STA operation 140.

There are several approaches for fixing or improving a failed path basedon the identified dominant feature of the path. In the example withmetal layer M3 being the dominant feature, a strategy in accordance withsome embodiments is to reroute at least a portion of the failed path ina different metal layer. A further strategy is to tune a manufacturingprocess to improve formation of interconnects in metal layer M3 and/orother metal layers around metal layer M3. Other correction strategiesare within the scopes of various embodiments. The described advantagesare not limited to the specific example with metal layer M3 as thedominant feature. Similar advantages are obtainable in one or moreembodiments with respect to paths and groups having other dominantfeatures, as described with respect to FIG. 2G or 3H.

Compared to other approaches, it is possible in some embodiments toidentify a larger number of paths to be tested, thereby increasing thelikelihood of locating and correcting small delay defects (SDDs) whilecovering a wide range of potential causes for SDDs. As described herein,SDDs involve small delay variations due to various factors including,but not limited to, fabrication process variations, power supply noise,crosstalk, or the like. In some situations, although delays atindividual cells or nets are small and within specifications, thecumulative delay of multiple such small delays, especially over a longpath, is potentially large enough to cause failure. In order to detect apotential SDD failure, other approaches select and test top criticalpaths, i.e., longest paths and/or paths with smallest slack based on anSTA timing report. Such an approach focuses on a narrow range of issuesand potentially results in a small number of paths selected for testingand/or being tested, without providing sufficient coverages for variouscauses for SDDs.

In contrast, in one or more embodiments, because the paths identifiedfor testing are directed to a wide range of features, as described withrespect to FIGS. 2G and 3H, a larger number of paths end up beingtested, while covering various potential causes for SDDs. At the sametime, critical paths covered by the other approaches are still coveredin one or more embodiments which include one or more groups of pathswith dominant features being timing features, including slack.

The wide coverage for potential causes for SDDs in at least oneembodiment makes it possible to locate and fix various systematicdefects which are one of the major challenges in advanced process nodes.Other approaches lack this capability. In some embodiments, furtheradvantages include, but are not limited to, distributed process defectcoverage for SDDs, ability to target any specific feature and/or processissue, independence of process nodes.

FIG. 5 is a flow chart of a method 500, in accordance with someembodiments. In at least one embodiment, method 500 is performed inwhole or in part by a processor as described herein.

At operation 505, a plurality of features of a plurality of paths in anintegrated circuit (IC) layout diagram is extracted. For example,features are extracted from at least one of a Verilog netlist containingan IC schematic corresponding to the IC layout diagram, one or more DEFand/or LEF files containing the IC layout diagram, a timing report of anSTA, or a library, as described with respect to FIG. 2G.

At operation 510, at least one feature is removed from the plurality offeatures to obtain a reduced set of features, based on a correlationcoefficient of the at least one feature with slack across the pluralityof paths and/or based on the at least one feature having no variation.For example, a correlation coefficient of each feature with slack acrossthe plurality of paths is calculated, as described with respect to FIG.3G. In response to the correlation coefficients of one or more featuresbeing within a predetermined range, the one or more features are removedfrom the plurality of features, resulting in a reduced set of features,as described with respect to FIG. 3H. In at least one embodiment,operation 510 is omitted, for example, when all features have variationsand the correlation coefficients of all features with slack across theplurality of paths are outside the predetermined range described withrespect to FIG. 3G.

At operation 515, the plurality of paths is clustered into a pluralityof clusters. For example, a clustering algorithm is applied to dividethe plurality of paths into a plurality of clusters, as described withrespect to the feature clustering operation 154 in FIG. 4.

At operation 520, a feature included in the reduced set of features isdetermined as a dominant feature for each cluster among the plurality ofclusters. For example, a dominant feature is determined for eachcluster, as described with respect to FIG. 4. A dominant feature is afeature by which paths in the cluster are dominated, for example, asdescribed with respect to FIGS. 2B-2F.

At operation 525, each cluster having the dominant feature differentfrom dominant features of other clusters is designated as a group ofpaths among a plurality of groups of paths to be created from theplurality of clusters, for example, as described with respect to theoperation 450 in FIG. 4.

At operation 530, clusters having the same dominant feature are mergedto obtain a further group among the plurality of groups, for example, asdescribed with respect to the operation 450 in FIG. 4.

At operation 535, the plurality of groups of paths is created from theplurality of paths in the IC layout diagram, where each group has adominant feature among the plurality of features of the plurality ofpaths, and the dominant features of the plurality of groups aredifferent from each other, for example, as a result of operations 525,530.

At operation 540, at least one test pattern is generated for at leastone path in each group among the plurality of groups. For example,automatic test pattern generation (ATPG) is performed to generate atleast one test pattern, as described with respect to the ATPG operation156 in FIG. 4.

At operation 545, at least one path in a group among the plurality ofgroups is tested. For example, the at least one path is tested by usingthe generated at least one test pattern in a simulation or by an ATE, asdescribed with respect to the testing operation 160 in FIG. 1.

At operation 550, in response to the testing indicating that the atleast one path fails, a modification is made to at least one of the IClayout diagram, at least a portion of at least one library having cellsincluded in the IC layout diagram, or a manufacturing process formanufacturing an IC corresponding to the IC layout diagram. For example,one or more corrections are made to at least one of the IC design, alibrary or a manufacturing process when a path failed, as described withrespect to the modification operation 170 in FIG. 1.

In at least one embodiment, all operations 505-550 are automaticallyperformed without user input or intervention.

The described methods include example operations, but they are notnecessarily required to be performed in the order shown. Operations maybe added, replaced, changed order, and/or eliminated as appropriate, inaccordance with the spirit and scope of embodiments of the disclosure.Embodiments that combine different features and/or different embodimentsare within the scope of the disclosure and will be apparent to those ofordinary skill in the art after reviewing this disclosure.

In some embodiments, at least one method(s) discussed above is performedin whole or in part by at least one EDA system. In some embodiments, anEDA system is usable as part of a design house of an IC manufacturingsystem discussed below.

FIG. 6 is a block diagram of an electronic design automation (EDA)system 600 in accordance with some embodiments.

In some embodiments, EDA system 600 includes an APR system. Methodsdescribed herein of designing layout diagrams represent wire routingarrangements, in accordance with one or more embodiments, areimplementable, for example, using EDA system 600, in accordance withsome embodiments.

In some embodiments, EDA system 600 is a general purpose computingdevice including a hardware processor 602 and a non-transitory,computer-readable storage medium 604. Storage medium 604, amongst otherthings, is encoded with, i.e., stores, computer program code 606, i.e.,a set of executable instructions. Execution of instructions 606 byhardware processor 602 represents (at least in part) an EDA tool whichimplements a portion or all of the methods described herein inaccordance with one or more embodiments (hereinafter, the notedprocesses and/or methods).

Processor 602 is electrically coupled to computer-readable storagemedium 604 via a bus 608. Processor 602 is also electrically coupled toan I/O interface 610 by bus 608. A network interface 612 is alsoelectrically connected to processor 602 via bus 608. Network interface612 is connected to a network 614, so that processor 602 andcomputer-readable storage medium 604 are capable of connecting toexternal elements via network 614. Processor 602 is configured toexecute computer program code 606 encoded in computer-readable storagemedium 604 in order to cause system 600 to be usable for performing aportion or all of the noted processes and/or methods. In one or moreembodiments, processor 602 is a central processing unit (CPU), amulti-processor, a distributed processing system, an applicationspecific integrated circuit (ASIC), and/or a suitable processing unit.

In one or more embodiments, computer-readable storage medium 604 is anelectronic, magnetic, optical, electromagnetic, infrared, and/or asemiconductor system (or apparatus or device). For example,computer-readable storage medium 604 includes a semiconductor orsolid-state memory, a magnetic tape, a removable computer diskette, arandom access memory (RAM), a read-only memory (ROM), a rigid magneticdisk, and/or an optical disk. In one or more embodiments using opticaldisks, computer-readable storage medium 604 includes a compact disk-readonly memory (CD-ROM), a compact disk-read/write (CD-R/W), and/or adigital video disc (DVD).

In one or more embodiments, storage medium 604 stores computer programcode 606 configured to cause system 600 (where such execution represents(at least in part) the EDA tool) to be usable for performing a portionor all of the noted processes and/or methods. In one or moreembodiments, storage medium 604 also stores information whichfacilitates performing a portion or all of the noted processes and/ormethods. In one or more embodiments, storage medium 604 stores library607 of standard cells including such standard cells as disclosed herein.

EDA system 600 includes I/O interface 610. I/O interface 610 is coupledto external circuitry. In one or more embodiments, I/O interface 610includes a keyboard, keypad, mouse, trackball, trackpad, touchscreen,and/or cursor direction keys for communicating information and commandsto processor 602.

EDA system 600 also includes network interface 612 coupled to processor602. Network interface 612 allows system 600 to communicate with network614, to which one or more other computer systems are connected. Networkinterface 612 includes wireless network interfaces such as BLUETOOTH,WIFI, WIMAX, GPRS, or WCDMA; or wired network interfaces such asETHERNET, USB, or IEEE-1364. In one or more embodiments, a portion orall of noted processes and/or methods, is implemented in two or moresystems 600.

System 600 is configured to receive information through I/O interface610. The information received through I/O interface 610 includes one ormore of instructions, data, design rules, libraries of standard cells,and/or other parameters for processing by processor 602. The informationis transferred to processor 602 via bus 608. EDA system 600 isconfigured to receive information related to a UI through I/O interface610. The information is stored in computer-readable medium 604 as userinterface (UI) 642.

In some embodiments, a portion or all of the noted processes and/ormethods is implemented as a standalone software application forexecution by a processor. In some embodiments, a portion or all of thenoted processes and/or methods is implemented as a software applicationthat is a part of an additional software application. In someembodiments, a portion or all of the noted processes and/or methods isimplemented as a plug-in to a software application. In some embodiments,at least one of the noted processes and/or methods is implemented as asoftware application that is a portion of an EDA tool. In someembodiments, a portion or all of the noted processes and/or methods isimplemented as a software application that is used by EDA system 600. Insome embodiments, a layout diagram which includes standard cells isgenerated using a tool such as VIRTUOSO® available from CADENCE DESIGNSYSTEMS, Inc., or another suitable layout generating tool.

In some embodiments, the processes are realized as functions of aprogram stored in a non-transitory computer readable recording medium.Examples of a non-transitory computer readable recording medium include,but are not limited to, external/removable and/or internal/built-instorage or memory unit, e.g., one or more of an optical disk, such as aDVD, a magnetic disk, such as a hard disk, a semiconductor memory, suchas a ROM, a RAM, a memory card, and the like.

FIG. 7 is a block diagram of an integrated circuit (IC) manufacturingsystem 700, and an IC manufacturing flow associated therewith, inaccordance with some embodiments. In some embodiments, based on a layoutdiagram, at least one of (A) one or more semiconductor masks or (B) atleast one component in a layer of a semiconductor integrated circuit isfabricated using manufacturing system 700.

In FIG. 7, IC manufacturing system 700 includes entities, such as adesign house 720, a mask house 730, and an IC manufacturer/fabricator(“fab”) 750, that interact with one another in the design, development,and manufacturing cycles and/or services related to manufacturing an ICdevice 760. The entities in system 700 are connected by a communicationsnetwork. In some embodiments, the communications network is a singlenetwork. In some embodiments, the communications network is a variety ofdifferent networks, such as an intranet and the Internet. Thecommunications network includes wired and/or wireless communicationchannels. Each entity interacts with one or more of the other entitiesand provides services to and/or receives services from one or more ofthe other entities. In some embodiments, two or more of design house720, mask house 730, and IC fab 750 is owned by a single larger company.In some embodiments, two or more of design house 720, mask house 730,and IC fab 750 coexist in a common facility and use common resources.

Design house (or design team) 720 generates an IC design layout diagram722. IC design layout diagram 722 includes various geometrical patternsdesigned for an IC device 760. The geometrical patterns correspond topatterns of metal, oxide, or semiconductor layers that make up thevarious components of IC device 760 to be fabricated. The various layerscombine to form various IC features. For example, a portion of IC designlayout diagram 722 includes various IC features, such as an activeregion, gate electrode, source and drain, metal lines or vias of aninterlayer interconnection, and openings for bonding pads, to be formedin a semiconductor substrate (such as a silicon wafer) and variousmaterial layers disposed on the semiconductor substrate. Design house720 implements a proper design procedure to form IC design layoutdiagram 722. The design procedure includes one or more of logic design,physical design or place-and-route operation. IC design layout diagram722 is presented in one or more data files having information of thegeometrical patterns. For example, IC design layout diagram 722 can beexpressed in a GDSII file format or DFII file format.

Mask house 730 includes data preparation 732 and mask fabrication 744.Mask house 730 uses IC design layout diagram 722 to manufacture one ormore masks 745 to be used for fabricating the various layers of ICdevice 760 according to IC design layout diagram 722. Mask house 730performs mask data preparation 732, where IC design layout diagram 722is translated into a representative data file (“RDF”). Mask datapreparation 732 provides the RDF to mask fabrication 744. Maskfabrication 744 includes a mask writer. A mask writer converts the RDFto an image on a substrate, such as a mask (reticle) 745 or asemiconductor wafer 753. The design layout diagram 722 is manipulated bymask data preparation 732 to comply with particular characteristics ofthe mask writer and/or requirements of IC fab 750. In FIG. 7, mask datapreparation 732 and mask fabrication 744 are illustrated as separateelements. In some embodiments, mask data preparation 732 and maskfabrication 744 can be collectively referred to as mask datapreparation.

In some embodiments, mask data preparation 732 includes opticalproximity correction (OPC) which uses lithography enhancement techniquesto compensate for image errors, such as those that can arise fromdiffraction, interference, other process effects and the like. OPCadjusts IC design layout diagram 722. In some embodiments, mask datapreparation 732 includes further resolution enhancement techniques(RET), such as off-axis illumination, sub-resolution assist features,phase-shifting masks, other suitable techniques, and the like orcombinations thereof. In some embodiments, inverse lithographytechnology (ILT) is also used, which treats OPC as an inverse imagingproblem.

In some embodiments, mask data preparation 732 includes a mask rulechecker (MRC) that checks the IC design layout diagram 722 that hasundergone processes in OPC with a set of mask creation rules whichcontain certain geometric and/or connectivity restrictions to ensuresufficient margins, to account for variability in semiconductormanufacturing processes, and the like. In some embodiments, the MRCmodifies the IC design layout diagram 722 to compensate for limitationsduring mask fabrication 744, which may undo part of the modificationsperformed by OPC in order to meet mask creation rules.

In some embodiments, mask data preparation 732 includes lithographyprocess checking (LPC) that simulates processing that will beimplemented by IC fab 750 to fabricate IC device 760. LPC simulates thisprocessing based on IC design layout diagram 722 to create a simulatedmanufactured device, such as IC device 760. The processing parameters inLPC simulation can include parameters associated with various processesof the IC manufacturing cycle, parameters associated with tools used formanufacturing the IC, and/or other aspects of the manufacturing process.LPC takes into account various factors, such as aerial image contrast,depth of focus (“DOF”), mask error enhancement factor (“MEEF”), othersuitable factors, and the like or combinations thereof. In someembodiments, after a simulated manufactured device has been created byLPC, if the simulated device is not close enough in shape to satisfydesign rules, OPC and/or MRC are be repeated to further refine IC designlayout diagram 722.

It should be understood that the above description of mask datapreparation 732 has been simplified for the purposes of clarity. In someembodiments, data preparation 732 includes additional features such as alogic operation (LOP) to modify the IC design layout diagram 722according to manufacturing rules. Additionally, the processes applied toIC design layout diagram 722 during data preparation 732 may be executedin a variety of different orders.

After mask data preparation 732 and during mask fabrication 744, a mask745 or a group of masks 745 are fabricated based on the modified ICdesign layout diagram 722. In some embodiments, mask fabrication 744includes performing one or more lithographic exposures based on ICdesign layout diagram 722. In some embodiments, an electron-beam(e-beam) or a mechanism of multiple e-beams is used to form a pattern ona mask (photomask or reticle) 745 based on the modified IC design layoutdiagram 722. Mask 745 can be formed in various technologies. In someembodiments, mask 745 is formed using binary technology. In someembodiments, a mask pattern includes opaque regions and transparentregions. A radiation beam, such as an ultraviolet (UV) beam, used toexpose the image sensitive material layer (e.g., photoresist) which hasbeen coated on a wafer, is blocked by the opaque region and transmitsthrough the transparent regions. In one example, a binary mask versionof mask 745 includes a transparent substrate (e.g., fused quartz) and anopaque material (e.g., chromium) coated in the opaque regions of thebinary mask. In another example, mask 745 is formed using a phase shifttechnology. In a phase shift mask (PSM) version of mask 745, variousfeatures in the pattern formed on the phase shift mask are configured tohave proper phase difference to enhance the resolution and imagingquality. In various examples, the phase shift mask can be attenuated PSMor alternating PSM. The mask(s) generated by mask fabrication 744 isused in a variety of processes. For example, such a mask(s) is used inan ion implantation process to form various doped regions insemiconductor wafer 753, in an etching process to form various etchingregions in semiconductor wafer 753, and/or in other suitable processes.

IC fab 750 is an IC fabrication business that includes one or moremanufacturing facilities for the fabrication of a variety of differentIC products. In some embodiments, IC Fab 750 is a semiconductor foundry.For example, there may be a manufacturing facility for the front endfabrication of a plurality of IC products (front-end-of-line (FEOL)fabrication), while a second manufacturing facility may provide the backend fabrication for the interconnection and packaging of the IC products(back-end-of-line (BEOL) fabrication), and a third manufacturingfacility may provide other services for the foundry business.

IC fab 750 includes fabrication tools 752 configured to execute variousmanufacturing operations on semiconductor wafer 753 such that IC device760 is fabricated in accordance with the mask(s), e.g., mask 745. Invarious embodiments, fabrication tools 752 include one or more of awafer stepper, an ion implanter, a photoresist coater, a processchamber, e.g., a CVD chamber or LPCVD furnace, a CMP system, a plasmaetch system, a wafer cleaning system, or other manufacturing equipmentcapable of performing one or more suitable manufacturing processes asdiscussed herein.

IC fab 750 uses mask(s) 745 fabricated by mask house 730 to fabricate ICdevice 760. Thus, IC fab 750 at least indirectly uses IC design layoutdiagram 722 to fabricate IC device 760. In some embodiments,semiconductor wafer 753 is fabricated by IC fab 750 using mask(s) 745 toform IC device 760. In some embodiments, the IC fabrication includesperforming one or more lithographic exposures based at least indirectlyon IC design layout diagram 722. Semiconductor wafer 753 includes asilicon substrate or other proper substrate having material layersformed thereon. Semiconductor wafer 753 further includes one or more ofvarious doped regions, dielectric features, multilevel interconnects,and the like (formed at subsequent manufacturing steps).

Details regarding an integrated circuit (IC) manufacturing system (e.g.,system 700 of FIG. 7), and an IC manufacturing flow associated therewithare found, e.g., in U.S. Pat. No. 9,256,709, granted Feb. 9, 2016, U.S.Pre-Grant Publication No. 20150278429, published Oct. 1, 2015, U.S.Pre-Grant Publication No. 20140040838, published Feb. 6, 2014, and U.S.Pat. No. 7,260,442, granted Aug. 21, 2007, the entireties of each ofwhich are hereby incorporated by reference.

In some embodiments, a method executed at least partially by a processorcomprises creating a plurality of groups of paths from a plurality ofpaths in an integrated circuit (IC) layout diagram. Each group among theplurality of groups has a dominant feature among a plurality of featuresof the plurality of paths. The dominant features of the plurality ofgroups are different from each other. The method further comprisestesting at least one path in a group among the plurality of groups. Themethod also comprises, in response to the testing indicating that the atleast one path fails, modifying at least one of the IC layout diagram,at least a portion of at least one library having cells included in theIC layout diagram, or a manufacturing process for manufacturing an ICcorresponding to the IC layout diagram.

In some embodiments, a system comprises a processor. The processor isconfigured to extract a plurality of features of a plurality of paths inan integrated circuit (IC) layout diagram. The processor is furtherconfigured to cluster the plurality of paths into a plurality ofclusters. The processor is further configured to, for each cluster amongthe plurality of clusters, determine a dominant feature for said eachcluster, the dominant feature included in the plurality of features. Theprocessor is further configured to, based on the dominant features ofthe plurality of clusters, create a plurality of groups of paths fromthe plurality of clusters, each group among the plurality of groupshaving a unique dominant feature among the dominant features. Theprocessor is further configured to, for each group among the pluralityof groups, perform automatic test pattern generation (ATPG) to generateat least one test pattern, and perform a test of at least one path insaid each group using the generated at least one test pattern. Theprocessor is further configured to, in response to the test indicatingthat the at least one path fails, cause modification of at least one ofthe IC layout diagram, at least a portion of at least one library havingcells included in the IC layout diagram, or a manufacturing process formanufacturing an IC corresponding to the IC layout diagram.

In some embodiments, a computer program product comprises anon-transitory, computer-readable medium containing instructionstherein. The instructions, when executed by a processor, cause theprocessor to create a plurality of groups of paths from a plurality ofpaths in an integrated circuit (IC) layout diagram, by clustering theplurality of paths into a plurality of clusters, determining a dominantfeature for each cluster among the plurality of clusters, the dominantfeature included in a plurality of features of the plurality of paths,designating each cluster having the dominant feature different fromdominant features of other clusters as a group among the plurality ofgroups, and merging clusters having the same dominant feature to obtaina further group among the plurality of groups. The instructions, whenexecuted, further cause the processor to perform a test of at least onepath in a group among the plurality of groups and, in response to the atleast one path failing the test, cause modification of at least one ofthe IC layout diagram, at least a portion of at least one library havingcells included in the IC layout diagram, or a manufacturing process formanufacturing an IC corresponding to the IC layout diagram.

The foregoing outlines features of several embodiments so that thoseskilled in the art may better understand the aspects of the presentdisclosure. Those skilled in the art should appreciate that they mayreadily use the present disclosure as a basis for designing or modifyingother processes and structures for carrying out the same purposes and/orachieving the same advantages of the embodiments introduced herein.Those skilled in the art should also realize that such equivalentconstructions do not depart from the spirit and scope of the presentdisclosure, and that they may make various changes, substitutions, andalterations herein without departing from the spirit and scope of thepresent disclosure.

1. A method, said method executed at least partially by a processor andcomprising: creating a plurality of groups of paths from a plurality ofpaths in an integrated circuit (IC) layout diagram, wherein each groupamong the plurality of groups has a dominant feature among a pluralityof features of the plurality of paths, and the dominant features of theplurality of groups are different from each other; testing at least onepath in a group among the plurality of groups; and in response to saidtesting indicating that the at least one path fails, modifying at leastone of: the IC layout diagram, at least a portion of at least onelibrary having cells included in the IC layout diagram, or amanufacturing process for manufacturing an IC corresponding to the IClayout diagram wherein the method further comprises removing at leastone feature from the plurality of features to obtain a reduced set offeatures including the dominant features of the plurality of groups. 2.The method of claim 1, wherein said modifying changes not only the atleast one path that fails said testing, but also other paths in the samegroup as the at least one path.
 3. The method of claim 1, furthercomprising: generating at least one test pattern for the at least onepath in said group, wherein said testing comprises testing the at leastone path using the generated at least one test pattern.
 4. The method ofclaim 1, wherein the plurality of features comprises at least one of:one or more timing features in a timing report of a static timinganalysis (STA) of the IC layout diagram, one or more logical features inan IC schematic corresponding to the IC layout diagram, or one or morephysical features of elements in the IC layout diagram.
 5. (canceled) 6.The method of claim 1, wherein in said removing, the at least oneremoved feature comprises a feature which has no variation across theplurality of paths.
 7. The method of claim 1, further comprising: foreach feature among the plurality of features, determining a correlationcoefficient between values of said feature in the plurality of paths,and values of slack in the plurality of paths, wherein in said removing,the at least one removed feature comprises features with the correlationcoefficients within a predetermined range.
 8. The method of claim 7,wherein the plurality of features comprises: numerical features havingnumerical values, and categorical features having non-numerical values,the method further comprising: converting non-numerical values of thecategorical features into converted numerical values; normalizing thenumerical values of the numerical features and the converted numericalvalues of the categorical features; and using the normalized values todetermine the correlation coefficient between slack and each featureamong the plurality of features.
 9. The method of claim 8, wherein thecategorical features comprise: pin names or instance names which, insaid converting, are converted into the corresponding convertednumerical values based on hierarchy levels associated with the pin namesor instance names, cell features which, in said converting, are splitinto cell function types and process parameters, and then the cellfunction types and the process parameters are converted into thecorresponding converted numerical values, and other features which, insaid converting, are converted into the corresponding convertednumerical values using ordinal encoding.
 10. The method of claim 1,wherein said creating the plurality of groups comprises: clustering theplurality of paths into a plurality of clusters, determining thedominant feature for each cluster among the plurality of clusters, andamong the plurality of clusters, designating each cluster having thedominant feature different from dominant features of other clusters as agroup among the plurality of groups, and merging clusters having thesame dominant feature to obtain a further group among the plurality ofgroups.
 11. The method of claim 10, wherein said determining thedominant feature for each cluster among the plurality of clusterscomprises: calculating CB_(nx)=(CM_(nx)−DS_(x))/DS_(x), where CB_(nx) isa biasing of feature x in cluster n, CM_(nx) is a mean value of featurex in the paths in cluster n, and DS_(x) is a mean value of feature x inthe plurality of paths, and in response to (CB_(nx)/Σ_(i=1) ^(m)C_(n)i)being greater than a predetermined threshold, determining that feature xis the dominant feature of cluster n, where the plurality of featuresincludes m features.
 12. The method of claim 11, wherein saiddetermining the dominant feature for each cluster among the plurality ofclusters further comprises: in response to no cluster having(CB_(nx)/Σ_(i=1) ^(m)C_(n)i) greater than the predetermined threshold,designating feature x as the dominant feature of the cluster with thegreatest (CB_(nx)/Σ_(i=1) ^(m)CB_(n)i).
 13. The method of claim 10,wherein said clustering comprises K-means clustering.
 14. A system,comprising a processor configured to: extract a plurality of features ofa plurality of paths in an integrated circuit (IC) layout diagram,cluster the plurality of paths into a plurality of clusters, for eachcluster among the plurality of clusters, calculate a biasing of eachfeature among the plurality of features, and based on the calculatedbiasing of each feature among the plurality of features, determine adominant feature for said each cluster, the dominant feature included inthe plurality of features, based on the dominant features of theplurality of clusters, create a plurality of groups of paths from theplurality of clusters, each group among the plurality of groups having aunique dominant feature among the dominant features, for each groupamong the plurality of groups, perform automatic test pattern generation(ATPG) to generate at least one test pattern, perform a test of at leastone path in said each group using the generated at least one testpattern, and in response to the test indicating that the at least onepath fails, cause modification of at least one of the IC layout diagram,at least a portion of at least one library having cells included in theIC layout diagram, or a manufacturing process for manufacturing an ICcorresponding to the IC layout diagram.
 15. The system of claim 14,wherein the processor is configured to extract the plurality of featuresas one or more timing features from a timing report of a static timinganalysis (STA) of the IC layout diagram, one or more logical featuresfrom an IC schematic corresponding to the IC layout diagram, and one ormore physical features of elements in the IC layout diagram.
 16. Thesystem of claim 14, wherein the processor is configured to remove afeature which has no variation across the plurality of paths from theplurality of features.
 17. The system of claim 14, wherein the pluralityof features comprises: numerical features having numerical values, andcategorical features having non-numerical values, the processor isfurther configured to convert non-numerical values of the categoricalfeatures into converted numerical values, normalize the numerical valuesof the numerical features and the converted numerical values of thecategorical features, use the normalized values to determine correlationcoefficients between the slack and the plurality of features, and removefeatures with the correlation coefficients within a predetermined rangefrom the plurality of features.
 18. A computer program product,comprising a non-transitory, computer-readable medium containinginstructions therein which, when executed by a processor, cause theprocessor to: create a plurality of groups of paths from a plurality ofpaths in an integrated circuit (IC) layout diagram, by clustering theplurality of paths into a plurality of clusters, determining a dominantfeature for each cluster among the plurality of clusters, the dominantfeature included in a plurality of features of the plurality of paths,the plurality of features including at least one of a physical dimensionof at least one element in the IC layout diagram, or slack of theplurality of paths, designating each cluster having the dominant featuredifferent from dominant features of other clusters as a group among theplurality of groups, and merging clusters having the same dominantfeature to obtain a further group among the plurality of groups, performa test of at least one path in a group among the plurality of groups;and in response to the at least one path failing the test, causemodification of at least one of: the IC layout diagram, at least aportion of at least one library having cells included in the IC layoutdiagram, or a manufacturing process for manufacturing an ICcorresponding to the IC layout diagram.
 19. The computer program productof claim 18, wherein the instructions, when executed by the processor,further cause the processor to: determine the dominant feature for eachcluster among the plurality of clusters by calculatingCB_(nx)=(CM_(nx)−DS_(x))/DS_(x), where CB_(nx) is a biasing of feature xin cluster n, CM_(nx) is a mean value of feature x in the paths incluster n, and DS_(x) is a mean value of feature x in the plurality ofpaths, and in response to (CB_(nx)/Σ_(i=1) ^(m)CB_(n)i) being greaterthan a predetermined threshold, determining that feature x is thedominant feature of cluster n, where the plurality of features includesm features, and in response to no cluster having (CB_(nx)/Σ_(i=1)^(m)CB_(n)i) greater than the predetermined threshold, designatingfeature x as the dominant feature of the cluster with the greatest(CB_(nx)/93 _(i=1) ^(m)C_(n)i).
 20. The computer program product ofclaim 18, wherein the instructions, when executed by the processor,further cause the processor to: perform K-means clustering forclustering the plurality of paths into the plurality of clusters. 21.The method of claim 1, further comprising: extracting, as one or morefeatures among the plurality of features, at least one of a physicaldimension of at least one element in the IC layout diagram, or slack ofthe plurality of paths.